What I did during my traineeship
During my stay at the University of Waterloo, I learned to use software for simulating neural processes, called Nengo. More specifically, this software allows the user to create networks of biologically realistic neurons that perform some user-specified computations. The main focus of my traineeship was a neural network, the Delay Network, that has been developed by researchers at the Computational Neuroscience group, led by Chris Eliasmith. Our hypothesis was that this network could account for some of empirical data in the psychological and neuroscience literature about how we perceive time. The results from our simulations indeed appear to confirm our hypothesis for several empirical phenomena, including one phenomenon that had resisted a satisfying explanation to our knowledge. Therefore, we wrote a six-page submission to the International Conference for Cognitive Modelling (ICCM), held in Montréal, and got accepted for an oral presentation. We also set up a continuing collaboration between the University of Groningen and University of Waterloo to further develop our model and write up a manuscript for publication in a scientific journal.

What I learned during my traineeship
Despite the steep learning curve of using Nengo, I managed to understand the software and underlying math to a degree that allowed me to integrate my preexisting knowledge of psychology and neuroscience smoothly. Further, my general programming skills in Python improved considerably and I am still learning to manage collaboration on software in GitHub.
Presenting at a conference taught me a lot of valuable scientific skills, such as collaboratively working on a page-length submission under time pressure. Also, I learned how to present complex ideas in an accessible manner and interact with other scientists who are working in similar fields or even in very different fields.